Promotion of solar energies usage in Iran: A scenario-based road map

Zanjirchi, Seyed Mahmoud; Shojaei, Sara; Sadrabadi, Alireza Naser; Jalilian, Negar

doi:10.1016/j.renene.2019.11.104

Cited by 20 publications

(7 citation statements)

References 37 publications

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“…The BMC is an increasingly used tool, in different fields, from identifying critical factors for rural development, to developing rural tourism, social agriculture or strategies for cooperatives [62,63]. It is generally used to describe business models in different industries [14,64].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Models Underlying the Success Development of Family Farms in Romania

Micu

Dumitru²,

Vintu

et al. 2022

Sustainability

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A family farm is an important part of the countryside, both economically and especially socially. In recent years, legislative measures have encouraged the development of large farms, ensuring food security while neglecting family farms, which are characterised by a lack of organisation, the absence of proper classification and the absence of measures to encourage their development and protection. In order to identify the premises underlying the development of family farms, and to create a development model for those family farms in a poor economic situation, the BMC method and SWOT analysis of seven family farms considered successful models were used. The development of these types of farms could provide a solution to a major problem facing the Romanian countryside: the depopulation of rural areas. The results of the study show that the development of these types of farms is based on joining an associative form (cooperatives) and/or making investments in the processing/storage line of agricultural products.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Models Underlying the Success Development of Family Farms in Romania

Micu

Dumitru²,

Vintu

et al. 2022

Sustainability

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“…MLR method tries to develop a relationship between a dependent variable and independent variables (the predictors) [80,81]. A simple relation for an MLR methodology is presented in Equation (1).…”

Section: Multiple Linear Regression (Mlr) and Logarithmic Multiple LImentioning

confidence: 99%

“…Energy is a vital need for contemporary human life and has profound impressions on social security, welfare as well as sturdy economic growth and development of a nation [1,2]. Despite the high cost and scarcity of energy [3], the growing world population has raised the global energy demand, especially in residential and commercial sectors.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors

et al. 2020

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Energy has a strategic role in the economic and social development of countries. In the last few decades, energy demand has been increasing exponentially across the world, and predicting energy demand has become one of the main concerns in many countries. The residential and commercial sectors constitute about 34.7% of global energy consumption. Anticipating energy demand in these sectors will help governments to supply energy sources and to develop their sustainable energy plans such as using renewable and non-renewable energy potentials for the development of a secure and environmentally friendly energy system. Modeling energy consumption in the residential and commercial sectors enables identification of the influential economic, social, and technological factors, resulting in a secure level of energy supply. In this paper, we forecast residential and commercial energy demands in Iran using three different machine learning methods, including multiple linear regression, logarithmic multiple linear regression methods, and nonlinear autoregressive with exogenous input artificial neural networks. These models are developed based on several factors, including the share of renewable energy sources in final energy consumption, gross domestic production, population, natural gas price, and the electricity price. According to the results of the three machine learning methods applied in our study, by 2040, Iranian residential and commercial energy consumption will be 76.97, 96.42 and 128.09 Mtoe, respectively. Results show that Iran must develop and implement new policies to increase the share of renewable energy supply in final energy consumption.

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“…The share of renewable energy in Iran’s total primary energy supply is less than 1%. A gradual shift of energy supply toward renewable energy and reducing consumption by improving energy efficiency can be considered effective solutions, which could be included in Iran’s future energy plan (Zanjirchi et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

Iran’s approach to energy policy towards 2040: a participatory scenario method

Hafezi

Heirani

Akbari

et al. 2023

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Purpose In the case of Iran, about 19 years have passed since the announcement of general energy policies. Policies adopted in the past included too many approaches and goals for the energy sector that some of them are in conflict with each other and their simultaneous implementation was impossible. Therefore, many of the expected goals of these policies have not been achieved. It is very important to adopt an appropriate approach that is compatible with the country’s characteristics and can steer energy policies. Therefore, this study aims to adopt an appropriate approach for the country’s energy sector according to the conditions and needs of the country. Design/methodology/approach A participatory scenario technique is designed and used to develop plausible projections in the case of Iran’s energy futures. Based on the proposed methodology, the research process starts with data gathering through interviews and national plans analysis. Then, findings were used as inputs to a simulation-based scenario development process. Scenarios are developed based on Monte Carlo simulation via cross-impact analysis technique purified based on expert judgments. Findings In this paper, to recognize Iran’s general approach to energy in the next 20 years, driving forces of change were introduced and used as input for the scenario development phase. Results showed sanctions play a significant role in Iran’s energy future and determine the directions of other driving forces. For renewable energy, it was proposed to increase the renewable share in Iran’s electricity generation mix to 5% of the total installed capacity. In the case of fossil fuel extraction, the maximum efficient rate was proposed for both oil and natural gas national production strategy. Originality/value This research is novel both in terms of application and theory. A new participatory scenario development method is used using simulations that are equipped based on experts’ judgments. Also from the practical perspective, this research targeted a future-oriented challenging problem to initialize national policy in a resource-rich developing economy (i.e. Iran).

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Promotion of solar energies usage in Iran: A scenario-based road map

Cited by 20 publications

References 37 publications

Models Underlying the Success Development of Family Farms in Romania

Models Underlying the Success Development of Family Farms in Romania

Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors

Iran’s approach to energy policy towards 2040: a participatory scenario method

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